Since PLS-MGA seems to be designed for comparing different groups (e.g., genders, cultures), I assume that the results are computed based on a independent sample t-test.

I collected panel data, and my goal is to investigate whether the strength of the path coefficients changes over time (e.g., some antecedents becoming more/less important over time). Now, the thing is that my samples are not independent, since the exact same participants completed the survey multiple times (3 weeks in between).

My question is whether I could still run the PLS-MGA, and then take parts of the output (e.g., interim results) to compute a dependent sample t-test for my purpose. If yes,a) which parts of the output do I need, b) which formula should I use with this output, and c) can I just use the basic PLS-MGA-settings or do I need to make changes?

Matthias, thanks for posting this question. Did you ever determine a good solution to the problem you described here with dependent samples and PLS-MGA? I am currently facing the same issue, wanting to compare path coefficients in a PLS model before and after an intervention. And thank you, Dr. Becker, for clarifying what Matthias suspected and confirming that MGA is not set up to account for this by default.